Built with and by Teycir Ben Soltane•
How to Use•FAQ•GitHub•arXiv.org•
Share:
ArXivCSExplorer
☆☆Bookmarks🏆RSSHow to UseFAQ
Home/Authors/Bingde Hu

Bingde Hu

3 indexed papers

Recent (6 mo)
3
With code
0
Influential cites
0
Benchmarked
0

Publications per year

3
26

Top categories

AI×3Crypto×2ML×2Info Retrieval×1

Frequent co-authors

Can Wang3×
Jiawei Chen3×
Runang He2×
Tongya Zheng2×
Huiling Peng2×
Yuanyu Wan2×

Research Timeline

2026
Temporal Motif-aware Graph Test-time Adaptation for OOD Blockchain Anomaly Detection

The paper proposes TEMG-TTA, a novel framework that uses temporal motif-aware graph test-time adaptation to significantly improve Out-of-Distribution (OOD) anomaly detection on complex cryptocurrency blockchains.

Temporal Motif-aware Graph Test-time Adaptation for OOD Blockchain Anomaly Detection

The paper proposes TEMG-TTA, a novel framework that combines temporal motif awareness and test-time adaptation to significantly improve Out-of-Distribution (OOD) anomaly detection in complex blockchain transaction graphs.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation

This paper proposes LBR, a framework to mitigate length bias in large language model-based recommendation systems.

Highlighted terms show continued research focus across papers

Papers

cs.IRcs.AIEmpiricalRecentJul 5, 2026

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation

Hongchen Li, Bohao Wang, Jingbang Chen, Weiqin Yang +4 more

This paper proposes LBR, a framework to mitigate length bias in large language model-based recommendation systems.

View →
cs.CRcs.AIcs.LGRecentMay 28, 2026

Temporal Motif-aware Graph Test-time Adaptation for OOD Blockchain Anomaly Detection

Runang He, Tongya Zheng, Huiling Peng, Yuanyu Wan +5 more

The paper proposes TEMG-TTA, a novel framework that uses temporal motif-aware graph test-time adaptation to significantly improve Out-of-Distribution (OOD) anomaly detection on complex cryptocurrency…

View →
cs.CRcs.AIcs.LGRecentMay 28, 2026

Temporal Motif-aware Graph Test-time Adaptation for OOD Blockchain Anomaly Detection

Runang He, Tongya Zheng, Huiling Peng, Yuanyu Wan +5 more

The paper proposes TEMG-TTA, a novel framework that combines temporal motif awareness and test-time adaptation to significantly improve Out-of-Distribution (OOD) anomaly detection in complex blockchai…

View →